Finding information in a textbook is an example of using the rational method of inquiry.
Collecting Qualitative Data: A Field Manual for Applied Research provides a very practical, step-by-step guide to collecting and managing
qualitative data. The data collection chapters focus on the three most often used forms of qualitative data collection: participant observation, in-depth interviews, and focus groups. The book also contains chapters on other practical aspects of qualitative field research often neglected in textbooks, including sampling, data management, research ethics, and supplementary data collection activities. Designed as an instructional field manual, this textbook includes many checklists and tips for
how to use each technique while doing research. It also includes numerous real-life examples and cases, making it easy for readers to see the broader picture. Qualitative Research: Defining and Designingqualitative research: Defining and designing The qualitative research methods introduced in this book are often employed to answer the whys and hows of human behavior, opinion, and experience—information that is difficult to obtain through more quantitatively-oriented methods of data collection. Researchers and practitioners in fields as diverse as anthropology, education, nursing, psychology, sociology, and marketing regularly use qualitative methods to address questions about people's ways of organizing, relating to, and interacting with the world. Despite the interdisciplinary recognition of the value of “qualitative research” (or perhaps because of it), qualitative research is not a unified field of theory and practice. On the contrary, a plethora of viewpoints, sometimes diametrically opposed to one another, exist on the subject. Scholars regularly debate ... locked icon Sign in to access this contentSign in Get a 30 day FREE TRIAL
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OverviewContent analysis is a research tool used to determine the presence of certain words, themes, or concepts within some given qualitative data (i.e. text). Using content analysis, researchers can quantify and analyze the presence, meanings, and relationships of such certain words, themes, or concepts. As an example, researchers can evaluate language used within a news article to search for bias or partiality. Researchers can then make inferences about the messages within the texts, the writer(s), the audience, and even the culture and time of surrounding the text. DescriptionSources of data could be from interviews, open-ended questions, field research notes, conversations, or literally any occurrence of communicative language (such as books, essays, discussions, newspaper headlines, speeches, media, historical documents). A single study may analyze various forms of text in its analysis. To analyze the text using content analysis, the text must be coded, or broken down, into manageable code categories for analysis (i.e. “codes”). Once the text is coded into code categories, the codes can then be further categorized into “code categories” to summarize data even further. Three different definitions of content analysis are provided below.
Uses of Content Analysis
Types of Content Analysis There are two general types of content analysis: conceptual analysis and relational analysis. Conceptual analysis determines the existence and frequency of concepts in a text. Relational analysis develops the conceptual analysis further by examining the relationships among concepts in a text. Each type of analysis may lead to different results, conclusions, interpretations and meanings. Conceptual Analysis Typically people think of conceptual analysis when they think of content analysis. In conceptual analysis, a concept is chosen for examination and the analysis involves quantifying and counting its presence. The main goal is to examine the occurrence of selected terms in the data. Terms may be explicit or implicit. Explicit terms are easy to identify. Coding of implicit terms is more complicated: you need to decide the level of implication and base judgments on subjectivity (an issue for reliability and validity). Therefore, coding of implicit terms involves using a dictionary or contextual translation rules or both. To begin a conceptual content analysis, first identify the research question and choose a sample or samples for analysis. Next, the text must be coded into manageable content categories. This is basically a process of selective reduction. By reducing the text to categories, the researcher can focus on and code for specific words or patterns that inform the research question. General steps for conducting a conceptual content analysis: 1. Decide the level of analysis: word, word sense, phrase, sentence, themes 2. Decide how many concepts to code for: develop a pre-defined or interactive set of categories or concepts. Decide either: A. to allow flexibility to add categories through the coding process, or B. to stick with the pre-defined set of categories.
3. Decide whether to code for existence or frequency of a concept. The decision changes the coding process.
4. Decide on how you will distinguish among concepts:
5. Develop rules for coding your texts. After decisions of steps 1-4 are complete, a researcher can begin developing rules for translation of text into codes. This will keep the coding process organized and consistent. The researcher can code for exactly what he/she wants to code. Validity of the coding process is ensured when the researcher is consistent and coherent in their codes, meaning that they follow their translation rules. In content analysis, obeying by the translation rules is equivalent to validity. 6. Decide what to do with irrelevant information: should this be ignored (e.g. common English words like “the” and “and”), or used to reexamine the coding scheme in the case that it would add to the outcome of coding? 7. Code the text: This can be done by hand or by using software. By using software, researchers can input categories and have coding done automatically, quickly and efficiently, by the software program. When coding is done by hand, a researcher can recognize errors far more easily (e.g. typos, misspelling). If using computer coding, text could be cleaned of errors to include all available data. This decision of hand vs. computer coding is most relevant for implicit information where category preparation is essential for accurate coding. 8. Analyze your results: Draw conclusions and generalizations where possible. Determine what to do with irrelevant, unwanted, or unused text: reexamine, ignore, or reassess the coding scheme. Interpret results carefully as conceptual content analysis can only quantify the information. Typically, general trends and patterns can be identified. Relational Analysis Relational analysis begins like conceptual analysis, where a concept is chosen for examination. However, the analysis involves exploring the relationships between concepts. Individual concepts are viewed as having no inherent meaning and rather the meaning is a product of the relationships among concepts. To begin a relational content analysis, first identify a research question and choose a sample or samples for analysis. The research question must be focused so the concept types are not open to interpretation and can be summarized. Next, select text for analysis. Select text for analysis carefully by balancing having enough information for a thorough analysis so results are not limited with having information that is too extensive so that the coding process becomes too arduous and heavy to supply meaningful and worthwhile results. There are three subcategories of relational analysis to choose from prior to going on to the general steps.
General steps for conducting a relational content analysis: 1. Determine the type of analysis: Once
the sample has been selected, the researcher needs to determine what types of relationships to examine and the level of analysis: word, word sense, phrase, sentence, themes.
4. Code the relationships: a difference between conceptual and relational analysis is that the statements or relationships between concepts are coded. Reliability and Validity Reliability: Because of the human nature of researchers, coding errors can never be eliminated but only minimized. Generally, 80% is an acceptable margin for reliability. Three criteria comprise the reliability of a content analysis:
Validity: Three criteria comprise the validity of a content analysis:
Advantages of Content Analysis
Disadvantages of Content Analysis
ReadingsTextbooks & Chapters
Methodological Articles
Application Articles
SoftwareChoosing whether to conduct a content analysis by hand or by using computer software can be difficult. Refer to ‘Method and Madness in the Application of Computer Technology to Qualitative Data Analysis’ listed above in “Textbooks and Chapters” for a discussion of the issue.
Websites
CoursesAt Columbia University’s Mailman School of Public Health, more detailed training is available through the Department of Sociomedical Sciences- P8785 Qualitative Research Methods. Which potential problem can occur the rational method is used?Which potential problem can occur when the rational method is used? People are not necessarily very good at logical reasoning.
Which method of acquiring knowledge is being used when people make decisions based on instinct or hunches?Intuition (or blinking) typically refers to the use of knowledge that is not explicit and in popular culture might be described as a “hunch” or “women's intuition.”
Which type of reasoning is more rational uses a more logical approach and relies on the scientific method?Rationalism. Rationalism involves using logic and reasoning to acquire new knowledge. Using this method premises are stated and logical rules are followed to arrive at sound conclusions.
What kind of reasoning uses a few specific observations to produce?Inductive reasoning begins with observations that are specific and limited in scope, and proceeds to a generalized conclusion that is likely, but not certain, in light of accumulated evidence. You could say that inductive reasoning moves from the specific to the general.
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